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Record W4281557765 · doi:10.33137/twpl.v44i1.36731

Acquisition of nominal and verbal number agreement in Brazilian Portuguese

2022· article· en· W4281557765 on OpenAlexvenueno aff
Marina Maia Reis

Bibliographic record

VenueToronto Working Papers in Linguistics · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsAgreementVariation (astronomy)PortugueseLinguisticsBrazilian PortugueseNoun phrasePsychologySet (abstract data type)Task (project management)NounPhraseProduction (economics)Natural language processingComputer sciencePhysicsEngineeringPhilosophy

Abstract

fetched live from OpenAlex

This study aims to investigate the acquisition of number agreement by Brazilian children. Since there is variation in expressing number agreement in Brazilian Portuguese (BP), it seeks to analyze the impact of linguistic variation on language acquisition. To this end, an experimental study was carried out. An elicited production task was conducted with monolingual children from three to five years of age acquiring BP, aiming to investigate how they produce number agreement in nominal elements and in verbs. Following Yang’s (2002) proposal, I suggest that the variation found in participants’ productions for the noun phrase could concern the acquisition of two grammars, with parameters set differently. On the other hand, the results found for verbal agreement seem to suggest that the variation observed in child production is a reflection of children’s linguistic development process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.288
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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